Gil Allouche

CEO at metadata.io | Helping B2B marketers automate paid campaigns 🦄 | We're hiring

A software engineer turned data-driven growth marketer, I founded metadata.io to make demand generation easy for non-technical marketers.

Metadata is a patented technology that combines predictive scoring and programmatic advertising to deliver a predictable pipeline of opt-in lead qualified leads for B2B enteprises. Among our customers: Cisco, UserVoice, Mulesoft, Salesforce, Infoblox, Aerospike and many others

Chief Executive Officer

AI Autonomous Marketing. 4 issued patents.
Inc #233 Fastest Growing Company 2020, 

Companies like Drift, Zoom, UIPath, Udacity and 100+ others rely on metadata.io to generate pipeline.

We just wrapped the first day of our Agentic GTM event and honestly… this was exactly what I hoped it would be.

Liza Adams kicked things off talking about how orgs are reimagining work in the AI era. Not 10% more efficient. Completely different.

Lisa Sharapata🌟 from our team spoke about the rise of Agentic GTM and the shift from prompts to pipeline.

The fireside chat with Amanda Cole from Bloomreach, Kimberly Storin from Zoom, and Natalie Scherer from LogicMonitor was the highlight. Three CMOs sharing how they're rebuilding their entire tech stacks. From automation to autonomy. No theory. Just what's actually working, what broke, and what they'd do differently.

Mary Gilbert (Kerford) challenged everything we think we know about brand. She measured how brands actually show up in AI-generated answers: 3% visibility, 0.3% citation rate. Most brands think they're invisible in the AI era, but the reality is they're perhaps becoming irrelevant.

Amanda Kahlow closed showing us what it looks like to scale with AI agents as first-class teammates.

Shoutout to our team, especially Lisa Sharapata🌟, for hosting the event and setting the stage for what turned into a really solid day.

To everyone who joined us online today: Thank you. Tomorrow's lineup and conversations are just as good!

Day 2:

Alina Vandenberghe 🌶️ on how Chili Piper hit $50M with 2 marketers. Matt Hammel on winning organic growth in the AI search era (SEO → AEO w/ AirOps). Tim Hillison on building an adaptable, self-learning agentic system. Dave Gerhardt from Exit Five on real B2B marketing vs. AI slop. Tim Sanders from G2 on building brand for AI search.

Plus fireside chats with Maura Rivera, Wendy W., and Brooke Cunningham.

Register for tomorrow here: https://lnkd.in/dBynJwFT

CEO at metadata.io | Making B2B Marketing Teams Predictable & Profitable 🦄

Three years ago, if you told a CMO that campaigns would run themselves, they'd have politely changed the subject.

Today, Trinity Nguyen 💎 at UserGems 💎 manages $2M in ad spend with one person. Alina Vandenberghe 🌶️ scaled Chili Piper to $50M with a two-person marketing team.

Instead of campaign managers coordinating between 12 platforms, they have systems that interpret strategic direction and execute across channels autonomously. Instead of analysts pulling reports to optimize campaigns, they have agents making 125+ optimizations daily without human intervention.

This December 3-5, we're bringing together the CMOs and VPs who made this transition to AI first.

Day 1 - The Shift: How organizations are fundamentally restructuring work in the AI era. Leaders from Zoom, LogicMonitor, Bloomreach, GrowthPath Partners, Infinite Edge Consulting, and 1mind share how they're rebuilding their stacks and scaling with AI.

Day 2 - Agentic GTM: Alina Vandenberghe shows exactly how Chili Piper's two-person team replaced eight specialists. Plus insights from AirOps, EntryPoint1, G2, Qualified, Comply, and LogicMonitor on building self-learning systems and preparing for the AI search era.

Day 3 - The Future: Trinity Nguyen on AI-powered ABM converting 10-15%. Live demos from Metadata's autonomous optimization system. Leaders from Clay, Clarity & Motion Collective, Docebo, and Fullcast on hybrid teams and customer acquisition strategies.

You'll see the workflows they use to brief AI agents. The guardrails for brand consistency. The new skills they hired for. The roles they eliminated. The metrics that matter when humans aren't touching every optimization.

Most importantly, the economic logic behind these decisions. Why these companies moved early and how they're thinking about competitive advantage.

If you're responsible for marketing infrastructure decisions, you need to understand what that game looks like before your competition does.

Join us: https://lnkd.in/dBynJwFT 

#AgenticGTM #MarketingOperations #AITransformation

You can only sit through so many ABM panels before you need a drink by a pool.

That's why we threw a party in the middle of 6sense Breakthrough. 

Metadata and Folloze (Etai Beck 👋) took over cabanas at the Fontainebleau Oasis Pool and told people: skip the sessions, come hang out with us instead.

The turnout blew us away. Marketing leaders from across the industry showed up, and the vibe was exactly what we hoped for. 

People weren't just networking, they were genuinely connecting. Swapping war stories about attribution models, comparing notes on what's actually driving the pipeline, talking about where AI fits into all of this without the usual conference theatrics.

That's what made it worth it. 

Not the cabanas or the Instagram moments. The fact that some of the sharpest people in B2B marketing chose to spend their afternoon with us instead of in another session hall.

To everyone who stopped by: thank you. The conversations, the energy, the genuine interest in where marketing is heading... that's what we're building for. 

Oh, and one more thing. Our AI agents made such an impression at the 6sense conference that security escorted them out of the casino. Worth it. 

Huge props to Lisa Sharapata🌟 for putting together the event and doing an amazing job at it!

And that's a wrap on three days of the Agentic GTM event.

Today, Trinity Nguyen 💎 from UserGems 💎 opened Day 3 with something sales teams actually care about - ABM that reps love and converts 10-15%. She showed their "Command Center" setup: CRM data, their proprietary signals, and third-party data feeding into one GTM Brain that coordinates both AI-assisted outbound reps and marketing.

James Silvestri from our team did a product showcase of Metadata's MVT/BID AGENT. He walked through the four core principles: autonomous execution, continuous learning, goal-oriented decision making, and agentic orchestration. Basically having a team of digital marketing specialists running 24/7.

Carol-Lyn Jardine talked about leading hybrid teams and brought a practical framework. She breaks work into four buckets - strategic work that's AI-assisted, strategic work that's AI-automated, tactical work that's AI-assisted, and tactical work that's fully automated. Her R4 Test helps you figure out what's actually ready to hand off to AI versus what still needs human judgment.

Bruno Estrella from Clay talked about how AI affects customer acquisition. His key insight: every GTM tactic loses effectiveness over time. The curve shows diminishing returns. You need systems that let you experiment faster than your tactics decay. That's where AI changes the game.

I closed with predictions for 2026. LLMs becoming the new operating system. AI improving drastically over the next two years - we're talking singularity territory. My advice: don't wait for AI to be 100% perfect. Start using it now. We currently have 71 AI agents that function as a full-stack B2B ad agency. You can literally automate your entire marketing operation with just words. 

Huge shoutout to Lisa Sharapata🌟, James Silvestri, and the entire Metadata team who made this happen. Three days, 20+ speakers, hundreds of attendees. 

To every speaker who showed up and shared what they're actually building, thank you for taking the time to share your valuable insights! 

And to everyone who attended, asked questions, shared resources in the chat, and stayed engaged across all three days - you made this what it was.

Reddit is quietly becoming one of the most important B2B demand channels.

If you manage revenue, you already know LinkedIn CPMs have climbed ~40% in 18 months.

Paid search costs are up as well.

The thing is that every channel is saturated with polished brand content except Reddit.

Reddit is where people talk about what they actually buy, what failed, and what replaced it.

The data’s messy, but the intent is clean.

CFOs discuss software rationalization.
CMOs ask peers which vendors survived their pipeline reviews.
And founders share which tools quietly keep them alive.

And no, it's not about Reddit being magical.

Reddit is one of the last places where buyers talk before they buy.

With MetadataONE, you can now apply firmographic and technographic filters to Reddit campaigns.

What it means is that you won't simply be advertising on Reddit.

You will be advertising to specific companies, titles, and buying committees, inside real conversations.

For CMOs and CROs thinking about next-year budgets, attention is fragmenting faster than spend.

The advantage now goes to whoever finds efficiency before the crowd calls it innovation.

6sense recently published a report arguing that the very phrase “intent data” has done more harm than good.

The same company that built a category around telling you which accounts are in-market now says most of those signals were just “digital loafing” on your website.

Think about what this means. 

For years, B2B teams bought intent data platforms expecting to identify accounts ready to buy. 

The pitch was clear: we’ll show you who’s in-market before they fill out a form. Sales could reach out at exactly the right moment.

Except the accounts weren’t in-market. They were researching. Browsing content. One person clicking around, not a buying committee evaluating vendors. SDRs reached out to “high intent” accounts and got nowhere. Sales stopped trusting marketing’s account lists. The promised pipeline never showed up.

Now 6sense is repositioning. Stop calling it intent, they say. Call it signals. Use it for marketing activation, not sales handoff. Treat interest as interest, not buying readiness.

That’s essentially admitting the core promise of ‘intent’ didn’t work the way it was sold.

First-party conversion signals matter more. The accounts that actually engage with your ads, consume your content, and convert on your site tell you more than any keyword surge or bidstream spike ever will.

The market is learning something important. Signals are useful for understanding attention. 

But attention alone isn’t intent. And it’s definitely not buying readiness. 

So what actually works? Systems that respond to real buying behavior, not interest spikes. That's Agentic GTM, essentially. More on that here: https://lnkd.in/gN8nPJMK

Day 2 wrapped successfully and we went from "why Agentic GTM matters" to Marketing Leaders showing us their actual tech stacks and the results they're seeing.

Alina Vandenberghe 🌶️ opened with the Chili Piper story. How they hit $50M with 2 marketers and a lot of agents. Her take: the CMO role is changing. Less campaign manager, more growth architect.

The fireside chat came next with Maura Rivera from Qualified, Wendy W. from Comply, and Brooke Cunningham from LogicMonitor. Three CMOs comparing notes on what they're betting on for 2026. What's working, what broke, and what they'd change.

Matt Hammel from AirOps walked through winning organic growth in the new world of AI search. One of his slides stood out to me for capturing something super critical: yesterday, huge expensive teams reached only a fraction of organic opportunities. Today, one AI-native IC can make 10x the impact. That’s essentially the shift from SEO to AEO summarized.

Tim Hillison walked through building self-learning agentic systems. He brought actual numbers. Like how connected systems lifted GTM revenue by 47%. One particular line of his stuck with me: "The internet gave us information. AI gives us decisions." 

Tim Sanders from G2 brought data on how buyers are already using AI search. 87% say it changed how they research. 50% start with AI search more than Google now. If your buyers made the leap, your brand strategy needs to catch up.

Dave Gerhardt closed with "The Anti-Slop Edge." In a world flooding with AI content, real B2B marketing becomes the differentiator. Felt like the right way to end Day 2.

What stood out today: the chat room. People were actively sharing resources, swapping tools, exchanging ideas. That energy made the day. 

A huge shoutout to Lisa Sharapata🌟 for doing a great job as always, and thanks to all the speakers and attendees for bringing their unique perspectives to the table and sharing the messy reality behind the scenes. 

Tomorrow’s the final day of our 3-day Agentic GTM virtual event, and we’ve an amazing line of speakers coming up as well. 

Coming up on Day 3:

Trinity Nguyen 💎 from UserGems 💎 opens with AI for ABM that reps actually love. James Silvestri from our team does a deep dive on Metadata's MVT/BID AGENT. Carol-Lyn Jardine talks about leading hybrid teams. David Brutman from Folloze on autonomous marketing. Bruno Estrella from Clay on how AI affects customer acquisition.

And I'll close out the event talking about what the future holds. See you tomorrow for the final day.

Register here if you haven't already: https://lnkd.in/dBynJwFT

Every generation watches their industry get completely reimagined. Marketing's turn is happening now.

The pattern is always the same: Infrastructure changes → middleman roles vanish → new capabilities emerge.

Travel: Physical agents → Direct booking platforms 
Photos: Darkroom technicians → Instagram filters 
Music: Record store clerks → Spotify algorithms 
Taxi: Dispatchers → Uber's automated matching

Marketing: Campaign coordinators → Prompt-to-pipeline systems

Each time, people said "but you need human expertise" and "but quality will suffer."

Sometimes they were right initially. Early digital photos looked worse than film. Early streaming had terrible selection.

But infrastructure improvements compound. Quality catches up, then exceeds what humans could do manually.

We're at that inflection point in marketing right now.

AI marketing isn't perfect yet. But manual coordination hit an unsolvable complexity ceiling. When you're managing 12+ platforms and campaign coordination takes weeks, AI execution doesn't need to be perfect. It just needs to be faster and more consistent than human bottlenecks.

This December 3-5, we're hosting the marketing leaders who've already made this shift.

Alina Vandenberghe 🌶️ got Chili Piper to $50M with 2 marketers and lots of agents. Not because agents were flawless, but because they removed the constraints holding her team back.

Manual processes create conservative constraints. When you can only manage 10 campaigns at a time, you pick the safest bets instead of the ones that might 100x your business. When your capacity maxes out at 50 data points, you can't run the 10,000 multivariate experiments that might reveal breakthrough insights.

The CMOs rebuilding their stacks understand this. Kimberly Storin at Zoom, Amanda Cole at Bloomreach, Natalie Scherer at LogicMonitor: they're figuring out how to move from automation to autonomy.

Matt Hammel from AirOps is showing how to win organic growth in the new world of AI search. Trinity Nguyen 💎 at UserGems 💎 is building AI for ABM that reps actually love. Bruno Estrella at Clay is exploring how AI affects customer acquisition.

And Dave Gerhardt is talking about what he calls "The Anti-Slop Edge": why real B2B marketing built on actual insight and authentic voice becomes the differentiator when everyone else is drowning in AI-generated sameness.

Two more days to go, we're hosting the leaders who've made this shift in our virtual event. Three days on how they rebuilt operations and where this is heading in 2026.

Join us virtually for FREE at: https://lnkd.in/dBynJwFT

Cross-channel marketing strategies consistently underperform when marketers default to replicating the same approach across every platform.

LinkedIn rewards professional targeting & industry-specific messaging. 
Google responds to intent-based keywords and search behavior. 
Facebook optimizes for behavioral signals and broader reach.

But a common trend I've noticed with a lot of B2B teams is to build audience structures in a single platform such as LinkedIn, and then replicate on others.

This leads to Facebook campaigns that target like LinkedIn but cost multiples more. And Google campaigns that ignore search intent while optimizing for impression share.

Cross-channel truly works when you build platform-native approaches that work together toward the same business outcome.

This means rebuilding campaign architecture for each channel's strength, and managing budget flow based on performance. Whether it might be doubling down on LinkedIn or cutting back on Google based on the performance of the campaigns. 

Which is why cross-channel is not really a strategy problem, but an execution one:

Building different structures that optimize for each platform while serving the same business goal without needing 10X the team size.

And this is exactly what MetadataONE does.

You describe your target audience once, and our AI agents create LinkedIn campaigns optimized for professional targeting, Facebook campaigns built for behavioral signals, and Google campaigns structured around search intent.
Budget flows automatically between channels based on which platform generates actual pipeline, not just clicks.

One strategy, platform-native execution, coordinated optimization.

(In the video below, Josh Desmarais and Lisa Sharapata🌟 break down how you can launch campaigns across multiple platforms: Meta, Google, Reddit, LinkedIn, along with various audience targeting options through MetadataONE)

The average marketing team switches between as many as 10 platforms to execute one campaign.

Each additional tool doesn't just add work; it actually multiplies it:

- More integrations
- More context switching
- More data transfer delays
- More places for data to break down

This means that a lot of B2B marketing stacks have to spend more time coordinating tools than executing campaigns.

Teams burn hours moving data between systems that should talk to each other.

When your tools are fragmented, your execution becomes fragmented too.

That’s why companies that are pulling ahead aren't optimizing individual platforms. They're eliminating tool complexity entirely.

Marketing infrastructure is consolidating the same way sales infrastructure did.

Salesforce didn't win by being better at contact management. It won by eliminating the need for multiple contact systems.

Even in marketing, single execution layers are replacing multi-platform orchestration.

When different tools don’t have to coordinate, it reduces the error margin by a huge number and helps teams move extraordinarily fast.

This is why MetadataONE connects directly to ChatGPT and Claude.

You can literally go from prompt to pipeline without switching platforms.

Your growth team spent 40 hours last month building campaigns that AI could launch in 40 minutes.

You see, marketing execution is collapsing under its own weight.

Thanks to the tedious process of:
* too many steps
* too many tools
* and too much friction between idea and launch

Growth leaders spend hours stitching audiences, creatives, and budgets across platforms.

That made sense when speed was limited by people.

But it doesn’t anymore.

The next generation of marketing ops isn’t about dashboards or workflow; it’s about instructions.

You just have to describe what you want.

AI builds, tests, and optimizes it in real time.

“Launch LinkedIn ads targeting CFOs in SaaS. Optimize by pipeline impact. And stop when CAC hits the threshold.”

With Metadata's MCP server, your single prompt generates the creative, configures targeting, and starts optimizing within minutes.

The same request that used to take a team of specialists now runs autonomously.

And the best thing is that it's faster, cheaper, and measurable against revenue.

Which means the real differentiator now is how precisely you can define outcomes.

You can literally run 1,200 ad experiments and get a better ROAS than your competitors while they're probably running just 30 ads.

Let me show you how…

Take 4 offers (case study, demo, whitepaper, video) × 5 channels (LinkedIn, Reddit, Facebook, AdWords, X) × 10 different copies × 3 creatives × 2 CTAs = 1,200 total combinations.

Your competitor's team would manually pick 30 "safe" variations, test them for two weeks, analyze results in spreadsheets, and pick a winner.

Meanwhile, if you use an agentic system like Metadata, it launches all 1,200 experiments on day one.

Within 48 hours, it identifies the top 200 performers based on early engagement signals. By day 7, it narrows to the best 100 based on cost-per-lead. By day 14, it knows which 25 campaigns actually convert to pipeline.

The system keeps going from there.

It fine-tunes experiments continuously, testing new variations of the winners. It adjusts bids 125+ times daily based on real-time performance. It refreshes audiences weekly as conversion data updates reveal better targeting opportunities. It automatically pauses underperformers, scales budget to winners, and tracks every experiment through to closed revenue.

Each cycle finds better combinations than the last. No compromising on experiment volume because of manual bandwidth. No picking "safe" campaigns because you can only manage a few tests. You can finally aim high without wasting time on tasks AI can solve today.

Two weeks later: Your competitor would have tested 30 campaigns and picked one winner. You would have run 1,200 experiments, identified 25 pipeline drivers, and the system would have already been optimizing the next iteration.

Manual coordination forces you to pick campaigns that won't fail while agentic systems let you discover campaigns that actually work.

Appreciate everyone who showed up and participated over the last three days👏🙏

That's a wrap.
Three days. Twenty-two speakers. Hundreds of marketers. One incredible event.

Day 3 of Agentic GTM brought it home.
Trinity Nguyen 💎 from UserGems 💎 showed us AI-powered ABM that converts and that sales reps actually love.

James Silvestri gave an exclusive deep dive into Metadata's MVT/BID agents. And showed us the art of what's possible when you let AI/ML do the mundane tasks and humans create the strategy and campaign concepts.

Carol-Lyn Jardine talked about leading hybrid teams. Because managing humans and AI agents together is a whole new leadership challenge.

David Brutman broke down autonomous marketing and what it means to redefine your entire GTM engine for the AI age.

Bruno Estrella from Clay explained how AI is fundamentally changing customer acquisition. Not just the tactics. The entire model.

And Gil Allouche closed us out with his predictions for 2026:

1. LLMs are the new operating system. They're not just tools. They're the foundation everything else is built on.
2. AI will improve drastically (aka Singularity) in the next 2 years. What's cutting-edge today will look primitive very soon.
3. Don't be left behind - Adopt generative AI in your work even if it isn't 100%. 
4. This is a tsunami / gold rush. Imagine it's 1991 before WWW took over. 

That's where we are right now.
Over three days, we heard from leaders who are already doing this. Who are rebuilding their stacks. Who are scaling with tiny teams. Who are winning in ways that weren't possible a year ago.

And the energy was incredible. The questions were sharp. The conversations were real.

To every speaker who shared their insights, their strategies, their mistakes, and their wins: thank you.

To every attendee who showed up, asked questions, and engaged with this community: thank you.

This is just the beginning.

If you missed any of the sessions, all recordings are available to registered attendees.

The future of GTM is being built right now. By people like you.
Let's go build it.

Marketing's job isn't demand generation anymore.

It's efficiency generation.

If you’re spending $200K/month on ads, your board doesn’t care about MQLs or impression volume.

They care about things like:
• CAC/LTV
• Pipeline per dollar
• Ad-spend/revenue 
• Cost per opportunity, not cost per lead
• How elastic your spending is when the market tightens

Most teams can’t answer any of that in real time because their execution is still manual.

They rebuild audiences across LinkedIn, Google, and Meta every quarter because nothing talks to each other.

Their attribution lives in spreadsheets, and creative refreshes take two weeks.

By the time they know what worked, the quarter's over.

Your bids should shift based on what your CRM says is working, not click-through rates.

Budgets should rebalance when campaigns stop creating actual opportunities.

Creative should rotate before it fatigues.

But none of that happens when your marketing stack is held together with exports and manual uploads.

MetadataONE connects directly to your revenue data and manages execution across channels automatically.

Rather than being another dashboard that explains what happened last week, it's an operating system that adjusts in real-time.

Because when the market contracts, and it certainly will, you'll want infrastructure, not spreadsheets.

We partnered with Nicole Havrda for F1! 

If you’re in Vegas come say hi and join us for some special festivities. (per available spots)

Lisa Sharapata🌟

Sourcing Revenue with B2B Marketers

Thrilled to be partnering with, and cheering for, Nicole Havrda - who's pushing forward  #F1Academy's mission to drive real change in motorsport and create a platform that inspires and supports more women in the sport.

Our partnership with her at Metadata feels natural and is a reflection of what we believe in.
Speed. Precision. Innovation. And the Human Drive to turn ambitious goals into real impact.

Excited for what's ahead - I'll be cheering along every step of the way!

Zoom cut their LinkedIn CPC by 77% by changing only one thing: 

Who was managing the bids. 

LinkedIn CPCs are up 8% year-over-year and CPLs are routinely exceeding $100 for B2B tech. 

Most marketers are responding by working harder. More hours in campaign manager. More manual bid adjustments. More spreadsheet gymnastics trying to squeeze efficiency out of campaigns that are fundamentally limited by human reaction time.

Zoom took a different approach.

Charisse Sare, their digital marketing lead, was facing the same pressure most CMOs face. Scaling global campaigns with fewer resources and tighter budgets. 

Instead of hiring more people, she handed bid optimization to Metadata's Bid Agent.

The Bid Agent made automatic bid adjustments every single day. Not once. Every day. 

Continuously watching auction dynamics and responding faster than any human could. 

The results after a clean A/B test: 

- CPC dropped 77%
- Impressions up 87%
- ROI went from 3.26x to 9x
- Influenced revenue up 177%

Charisse said it best: “It’s the most set-it-and-forget-it thing out there. Except the agent doesn’t forget.”

She estimates her team saves 3 to 10 hours per week now. That time went straight back into strategic work, creative projects, and campaign planning.

This is what we built Metadata to do. Get the repetitive stuff off your plate so you can focus on the problems only humans can solve.

How do you manage $50M in revenue with just 2 marketers?

Most people would say that you can’t. And that’s when I’d introduce them to Chili Piper.

Their secret isn’t incredible efficiency, it’s something entirely different…

While most companies focus on optimizing human processes, Alina Vandenberghe 🌶️ Vandenberghe has replaced them altogether.

Instead of analysts pulling reports to optimize campaigns, she has agents making 125+ optimizations daily without human intervention.

No campaign managers are coordinating across platforms, no analyst is pulling reports, and no creative teams are iterating ad variations.

The AI handles execution, whereas humans handle strategy and optimization.

Trinity Nguyen 💎 at UserGems 💎 manages $2M in ad spend the same way. One person, multiple AI agents handling the tactical work.

The decision-making happens daily, not quarterly.

When the system identifies a 15% CAC improvement, the budget shifts automatically. When new lookalike audiences show promise, they scale within hours.

Most marketing teams schedule meetings to discuss what the data means. These teams deploy systems that act on what the data shows.

This is the difference between managing people and managing systems.

December 3-5, Alina and Trinity are walking through their actual workflows.

The org decisions, daily processes, and infrastructure choices that most people never see.

Join us for the virtual session here: https://lnkd.in/dBynJwFT

This was the highlight of the Vegas event!! 

Thank you Lisa Sharapata🌟for organizing this awesome marketing play 😎. Marketing is fun.

Also big thanks to our friends at Folloze and to all of the dozens of marketers who came by to hang out with us at the Cabanas by the pool for an escape.

We got kicked out of #6senseBreakthrough. Here's why.

You heard that right. Our AI Agents made such a splash at the Fountainbleau this week they were escorted out by security!

But the real story isn't about getting kicked out. It's about the incredible marketing leaders we connected with at the Oasis pool cabanas. 

The energy was electric, and the conversations were even better.

We're fired up about the future of B2B marketing and our new partnership with Folloze. 

Together with Metadata ONE, we're not just part of the revolution – we're leading it.

A huge thank you to everyone who stopped by. If you missed us, let's connect!

#AI #MarketingLeaders  #MarketingRevolution

Yesssss great first day of the Agentic GTM event. 

Join hundreds of b2b marketers and GTM leaders for another myriad of sessions tomorrow !

🚨 Day 1 of the Agentic GTM event just wrapped.

Hundreds of marketers showed up. And the conversations were incredible.

Liza Adams talked about how orgs are reimagining work in the AI era. Not 10% more efficient. Completely different.

Lisa Sharapata🌟 Covered the rise of Agentic GTM and the shift from Prompts --> Pipeline

Amanda Cole, Kimberly Storin, and Natalie Scherer shared how they're rebuilding their entire tech stacks. From automation to autonomy.

Mary Gilbert (Kerford) Gilbert challenged everything we think we know about brand. (Spoiler: it's not about awareness anymore.)

And Amanda Kahlow showed us what it looks like to scale with AI agents as first-class teammates.

****It's not too late to join******
We still have 2 days left. And the lineup is insane.

Tomorrow (Day 2):
• Alina Vandenberghe 🌶️ Vandenberghe on how Chili Piper hit $50M with 2 marketers
• Matt Hammel on winning organic growth in the AI search era 
(SEO--> AEO w/ AirOps)
• Tim Hillison: Building an Adaptable, Self-Learning Agentic System
• Dave Gerhardt, Exit Five on real B2B marketing vs. AI slop
• Tim Sanders from G2 on building brand for AI search

• Plus fireside chats with Maura Rivera, Wendy W., and Brooke Cunningham


Thursday (Day 3):
• Trinity Nguyen 💎 UserGems 💎 on AI-powered ABM that converts at 10-15%
• James Silvestri's deep dive into Metadata's MVT/BID agents
• Carol-Lyn Jardine on leading hybrid teams
• David Brutman Co-founder at Folloze on Redefining the GTM Engine for the AI Age
• Bruno Estrella, from Clay on how AI is changing customer acquisition

Closing it out is Gil Allouche, CEO and Founder of Metadata to share his predictions on what the future holds. 

And if you register now, you get all 3 days of recordings. Including today.
So you won't miss anything.

This is happening right now. Companies are scaling with tiny teams. 

CMOs are rebuilding their stacks. 

AI agents are running campaigns at a scale that was impossible 6 months ago.

Don't get left behind.

Register here: https://lnkd.in/ecPVXt8z

What if you could test every ad variable simultaneously - bids, audiences, creatives, copy, CTAs, ad types - and let the system optimize itself?

That's what Metadata does and here's how it works:

Say you start with 100 ad variants across channels. Let's say your baseline CAC is $47.

Metadata's AI agents launch combinations across every layer - testing different bid strategies to find the lowest cost for the same result, rotating audiences weekly to keep targeting fresh, mixing creatives and copy to see what resonates.

Not 3-5 careful tests. 100 simultaneous experiments running live traffic.

Within days, the platform identifies which combinations actually drive conversions at the lowest cost.

It's not optimizing for CTR or engagement. It's tracking every click through to actual pipeline contribution.

The winning segments drop CAC to $44.

Then comes the interesting part.

Instead of guessing what "good audiences" look like, Metadata takes the winning campaign data and builds lookalike audiences across channels - finding similar profiles to the people who actually converted.

CAC drops to $41.

Finally, the system automatically shifts budget from underperforming variants to these optimized segments.

No manual budget reallocation meetings. No waiting for "enough data" to make decisions.

CAC hits $38.

Now comes the compound effect: Metadata doesn't stop. It takes those new $38 winners, builds fresh lookalikes, and launches the next round of variants.

Each cycle finds better audiences than the last.

Manual optimization finds what works once. Agentic optimization builds on what works repeatedly.

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Gil Allouche's LinkedIn Performance

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Gil Allouche's Best Posts (last 30 days)